This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations)
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Updated
Dec 6, 2021 - MATLAB
This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations)
The project aims to segment images into rover, background, and shadow. It starts with initial segmentation using SLIC and adaptive SLIC, followed by applying a Region Adjacency Graph (RAG). To address over-segmentation, Hierarchical Merging and Normalized Cuts are used.
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